Los Alamos National LaboratoryInformation Science and Technology Institute (ISTI)
Implementing and fostering collaborative research, workforce and program development, and technical exchange

Applied Machine Learning Summer Research Fellowship

Creating Next-Generation Leaders in Machine Learning
September 13, 2017
AML Group


  • Program Lead
  • Nick Lubbers
  • Program Co-Lead
  • Youzuo Lin
  • Program Co-Lead
  • Lissa Moore
  • Program Co-Lead
  • Diane Oyen
  • Administrative Assistant
  • Brittney Vigil

School Inquiries  

The Applied Machine Learning Summer Research Fellowship is an intense 10 week program aimed at providing graduate students with a solid foundation in modern machine learning through applications of importance to the National Lab and the world. Projects include developing methodologies to address practical use of machine learning including scalability, transparency, robustness and extendibility. Projects will apply machine learning to problems relating to interpretability, physics-informed learning, earth sciences, and uncertainty quantification. This is a paid fellowship that includes reimbursement for travel expenses.

The program is sponsored by the Information Science and Technology Institute (ISTI).


Research Fellows will learn hands-on by engaging in scientific research using machine learning. Research will be performed in small collaborations, guided by mentors with scientific and computational expertise.

See list of projects with descriptions.

Students will work on high performance computing clusters, apply practical ML tools, and gain experience in communicating their work through discussions and presentations. Students will attend seminars by LANL researchers and external visitors. We aim for high-impact summer projects that will lead to peer-reviewed, co-authored publications.


This multidisciplinary program is designed for graduate and upper-level undergraduate students from all science, math, computer science, and technology fields who are seeking to incorporate machine learning into their research careers. As a general guideline, students should have a background in one of the following: probability theory, statistical methods, algorithms, or statistical learning. Experience with programming and machine learning packages is encouraged. Specific skills needed for each project are listed in the project descriptions and the application form asks which projects you are most interested in.


To apply, you will need to submit the following materials:

  • Letter of intent stating strengths, goals, interests, and how the AML fellowship will help you achieve your goals
  • Current resume / CV
  • Unofficial university transcripts (official transcripts will be required if a position is offered and accepted)
  • Letter of recommendation from a faculty member

Please apply at the following link:

Apply now!

Application Deadline- January 15th, 2021. (Late applications may be submitted, but may not receive full consideration.)

Duration & Location

The 2021 program has a start date of June 7th, 2021, and lasts for 10 weeks. (Some flexibility on precise start and end dates may be afforded for extenuating circumstances).

AML 2021 will take place as a “Virtual Fellowship Program”; Fellows will work remotely and collaborate with mentors via teleconference and electronic collaboration tools.

Eligibility Requirements

  • Must be accepted to or enrolled in a graduate degree program
  • Must have and maintain a cumulative G.P.A. of 3.2/4.0 or better
  • Must be available to live and work in the United States.


More information about jobs and careers at Los Alamos. Or, take a look at other ISTI summer programs for students.

See our FAQs page, or if your question isn’t covered, you can contact us.